


from typing import Any



class A__     :



  """simple docstring"""



  def __init__( self			:  Union[str, Any]				,				lowerCamelCase__			:  Any       ):
        a__	:  List[str]     =   data
        a__	:  List[Any]     =   None

  def __repr__( self			:  Tuple       ):
        return f'''Node({self.data})'''




class A__     :



  """simple docstring"""



  def __init__( self			:  Dict       ):
        a__	:  Union[str, Any]     =   None

  def __iter__( self			:  List[Any]       ):
        a__	:  List[str]     =   self.head
        while node:
              yield node.data
              a__	:  List[Any]     =   node.next

  def __len__( self			:  Optional[Any]       ):
        return sum(1 for _ in self       )

  def __repr__( self			:  List[Any]       ):
        return "->".join([str(lowerCamelCase__       ) for item in self]       )

  def __getitem__( self			:  Dict				,				lowerCamelCase__			:  int       ):
        if not 0 <= index < len(self       ):
              raise ValueError("list index out of range."       )
        for i, node in enumerate(self       ):
              if i == index:
                    return node
        return None

  def __setitem__( self			:  Union[str, Any]				,				lowerCamelCase__			:  int				,				lowerCamelCase__			:  Any       ):
        if not 0 <= index < len(self       ):
              raise ValueError("list index out of range."       )
        a__	:  int     =   self.head
        for _ in range(lowerCamelCase__       ):
              a__	:  Union[str, Any]     =   current.next
        a__	:  Optional[int]     =   data

  def    _UpperCamelCase( self			:  Any				,				lowerCamelCase__			:  Any       ):
        self.insert_nth(len(self       )				,				lowerCamelCase__       )

  def    _UpperCamelCase( self			:  str				,				lowerCamelCase__			:  Any       ):
        self.insert_nth(0				,				lowerCamelCase__       )

  def    _UpperCamelCase( self			:  Union[str, Any]				,				lowerCamelCase__			:  int				,				lowerCamelCase__			:  Any       ):
        if not 0 <= index <= len(self       ):
              raise IndexError("list index out of range"       )
        a__	:  Union[str, Any]     =   Node(lowerCamelCase__       )
        if self.head is None:
              a__	:  List[Any]     =   new_node
        elif index == 0:
              a__	:  str     =   self.head  # link new_node to head
              a__	:  int     =   new_node
        else:
              a__	:  List[Any]     =   self.head
              for _ in range(index - 1       ):
                    a__	:  Optional[int]     =   temp.next
              a__	:  Optional[int]     =   temp.next
              a__	:  Dict     =   new_node

  def    _UpperCamelCase( self			:  List[Any]       ):  # print every node data
        print(self       )

  def    _UpperCamelCase( self			:  List[str]       ):
        return self.delete_nth(0       )

  def    _UpperCamelCase( self			:  Dict       ):  # delete from tail
        return self.delete_nth(len(self       ) - 1       )

  def    _UpperCamelCase( self			:  Any				,				lowerCamelCase__			:  int = 0       ):
        if not 0 <= index <= len(self       ) - 1:  # test if index is valid
              raise IndexError("List index out of range."       )
        a__	:  Optional[int]     =   self.head  # default first node
        if index == 0:
              a__	:  Tuple     =   self.head.next
        else:
              a__	:  List[Any]     =   self.head
              for _ in range(index - 1       ):
                    a__	:  int     =   temp.next
              a__	:  Tuple     =   temp.next
              a__	:  int     =   temp.next.next
        return delete_node.data

  def    _UpperCamelCase( self			:  Optional[int]       ):
        return self.head is None

  def    _UpperCamelCase( self			:  Optional[int]       ):
        a__	:  Any     =   None
        a__	:  List[Any]     =   self.head

        while current:
              # Store the current node's next node.
              a__	:  Tuple     =   current.next
              # Make the current node's next point backwards
              a__	:  int     =   prev
              # Make the previous node be the current node
              a__	:  Optional[Any]     =   current
              # Make the current node the next node (to progress iteration)
              a__	:  Tuple     =   next_node
        # Return prev in order to put the head at the end
        a__	:  Optional[Any]     =   prev




def UpperCamelCase_				(				)	->   None:
      a__	:  Tuple     =   LinkedList()
      assert linked_list.is_empty() is True
      assert str(__a      ) == ""

      try:
            linked_list.delete_head()
            raise AssertionError  # This should not happen.
      except IndexError:
            assert True  # This should happen.

      try:
            linked_list.delete_tail()
            raise AssertionError  # This should not happen.
      except IndexError:
            assert True  # This should happen.

      for i in range(10      ):
            assert len(__a      ) == i
            linked_list.insert_nth(__a			,				i + 1      )
      assert str(__a      ) == "->".join(str(__a      ) for i in range(1			,				11      )      )

      linked_list.insert_head(0      )
      linked_list.insert_tail(11      )
      assert str(__a      ) == "->".join(str(__a      ) for i in range(0			,				12      )      )

      assert linked_list.delete_head() == 0
      assert linked_list.delete_nth(9      ) == 10
      assert linked_list.delete_tail() == 11
      assert len(__a      ) == 9
      assert str(__a      ) == "->".join(str(__a      ) for i in range(1			,				10      )      )

      assert all(linked_list[i] == i + 1 for i in range(0			,				9      )      ) is True

      for i in range(0			,				9      ):
            a__	:  int     =   -i
      assert all(linked_list[i] == -i for i in range(0			,				9      )      ) is True

      linked_list.reverse()
      assert str(__a      ) == "->".join(str(__a      ) for i in range(-8			,				1      )      )



def UpperCamelCase_				(				)	->   None:
      a__	:  Union[str, Any]     =   [
          -9,
          100,
          Node(77_345_112      ),
          "dlrow olleH",
          7,
          5_555,
          0,
          -192.55555,
          "Hello, world!",
          77.9,
          Node(10      ),
          None,
          None,
          12.20,
      ]
      a__	:  Any     =   LinkedList()

      for i in test_input:
            linked_list.insert_tail(__a      )

      # Check if it's empty or not
      assert linked_list.is_empty() is False
      assert (
          str(__a      ) == "-9->100->Node(77345112)->dlrow olleH->7->5555->0->"
          "-192.55555->Hello, world!->77.9->Node(10)->None->None->12.2"
      )

      # Delete the head
      a__	:  int     =   linked_list.delete_head()
      assert result == -9
      assert (
          str(__a      ) == "100->Node(77345112)->dlrow olleH->7->5555->0->-192.55555->"
          "Hello, world!->77.9->Node(10)->None->None->12.2"
      )

      # Delete the tail
      a__	:  List[Any]     =   linked_list.delete_tail()
      assert result == 12.2
      assert (
          str(__a      ) == "100->Node(77345112)->dlrow olleH->7->5555->0->-192.55555->"
          "Hello, world!->77.9->Node(10)->None->None"
      )

      # Delete a node in specific location in linked list
      a__	:  List[str]     =   linked_list.delete_nth(10      )
      assert result is None
      assert (
          str(__a      ) == "100->Node(77345112)->dlrow olleH->7->5555->0->-192.55555->"
          "Hello, world!->77.9->Node(10)->None"
      )

      # Add a Node instance to its head
      linked_list.insert_head(Node("Hello again, world!"      )      )
      assert (
          str(__a      )
          == "Node(Hello again, world!)->100->Node(77345112)->dlrow olleH->"
          "7->5555->0->-192.55555->Hello, world!->77.9->Node(10)->None"
      )

      # Add None to its tail
      linked_list.insert_tail(__a      )
      assert (
          str(__a      )
          == "Node(Hello again, world!)->100->Node(77345112)->dlrow olleH->"
          "7->5555->0->-192.55555->Hello, world!->77.9->Node(10)->None->None"
      )

      # Reverse the linked list
      linked_list.reverse()
      assert (
          str(__a      )
          == "None->None->Node(10)->77.9->Hello, world!->-192.55555->0->5555->"
          "7->dlrow olleH->Node(77345112)->100->Node(Hello again, world!)"
      )



def UpperCamelCase_				(				)	->   Tuple:
      from doctest import testmod

      testmod()

      a__	:  Any     =   LinkedList()
      linked_list.insert_head(input("Inserting 1st at head "      ).strip()      )
      linked_list.insert_head(input("Inserting 2nd at head "      ).strip()      )
      print("\nPrint list:"      )
      linked_list.print_list()
      linked_list.insert_tail(input("\nInserting 1st at tail "      ).strip()      )
      linked_list.insert_tail(input("Inserting 2nd at tail "      ).strip()      )
      print("\nPrint list:"      )
      linked_list.print_list()
      print("\nDelete head"      )
      linked_list.delete_head()
      print("Delete tail"      )
      linked_list.delete_tail()
      print("\nPrint list:"      )
      linked_list.print_list()
      print("\nReverse linked list"      )
      linked_list.reverse()
      print("\nPrint list:"      )
      linked_list.print_list()
      print("\nString representation of linked list:"      )
      print(__a      )
      print("\nReading/changing Node data using indexing:"      )
      print(f'''Element at Position 1: {linked_list[1]}'''      )
      a__	:  Optional[int]     =   input("Enter New Value: "      ).strip()
      print("New list:"      )
      print(__a      )
      print(f'''length of linked_list is : {len(__a      )}'''      )


if __name__ == "__main__":
    main()







"""simple docstring"""




from typing import Dict

import numpy as np

from ..utils import add_end_docstrings, is_tf_available, is_torch_available, logging
from .base import PIPELINE_INIT_ARGS, GenericTensor, Pipeline, PipelineException


if is_tf_available():
					import tensorflow as tf

					from ..tf_utils import stable_softmax


if is_torch_available():
					import torch


lowerCAmelCase				:     int					=				logging.get_logger(__name__)






@add_end_docstrings(
    UpperCAmelCase__		,   R"\n        top_k (`int`, defaults to 5):\n            The number of predictions to return.\n        targets (`str` or `List[str]`, *optional*):\n            When passed, the model will limit the scores to the passed targets instead of looking up in the whole\n            vocab. If the provided targets are not in the model vocab, they will be tokenized and the first resulting\n            token will be used (with a warning, and that might be slower).\n\n    "		,   )
class        __magic_name__				(			UpperCAmelCase__							):






				'''simple docstring'''





				def   _lowerCAmelCase							(			self						,					_a					):





							"""simple docstring"""
							if self.framework == "tf":
										lowerCamelCase      =   tf.where(input_ids == self.tokenizer.mask_token_id					).numpy()
							elif self.framework == "pt":
										lowerCamelCase      =   torch.nonzero(input_ids == self.tokenizer.mask_token_id						,					as_tuple=_a					)
							else:
										raise ValueError("""Unsupported framework"""					)
							return masked_index





				def   _lowerCAmelCase							(			self						,					_a					):





							"""simple docstring"""
							lowerCamelCase      =   self.get_masked_index(_a					)
							lowerCamelCase      =   np.prod(masked_index.shape					)
							if numel < 1:
										raise PipelineException(
										    """fill-mask"""						,					self.model.base_model_prefix						,					f'No mask_token ({self.tokenizer.mask_token}) found on the input'						,					)





				def   _lowerCAmelCase							(			self						,					_a					):





							"""simple docstring"""
							if isinstance(_a						,					_a					):
										for model_input in model_inputs:
													self._ensure_exactly_one_mask_token(model_input["""input_ids"""][0]					)
							else:
										for input_ids in model_inputs["input_ids"]:
													self._ensure_exactly_one_mask_token(_a					)





				def   _lowerCAmelCase							(			self						,					_a						,					_a=None						,					**_a					):





							"""simple docstring"""
							if return_tensors is None:
										lowerCamelCase      =   self.framework
							lowerCamelCase      =   self.tokenizer(_a						,					return_tensors=_a					)
							self.ensure_exactly_one_mask_token(_a					)
							return model_inputs





				def   _lowerCAmelCase							(			self						,					_a					):





							"""simple docstring"""
							lowerCamelCase      =   self.model(**_a					)
							lowerCamelCase      =   model_inputs["""input_ids"""]
							return model_outputs





				def   _lowerCAmelCase							(			self						,					_a						,					_a=5						,					_a=None					):





							"""simple docstring"""
							# Cap top_k if there are targets
							if target_ids is not None and target_ids.shape[0] < top_k:
										lowerCamelCase      =   target_ids.shape[0]
							lowerCamelCase      =   model_outputs["""input_ids"""][0]
							lowerCamelCase      =   model_outputs["""logits"""]

							if self.framework == "tf":
										lowerCamelCase      =   tf.where(input_ids == self.tokenizer.mask_token_id					).numpy()[:, 0]

										lowerCamelCase      =   outputs.numpy()

										lowerCamelCase      =   outputs[0, masked_index, :]
										lowerCamelCase      =   stable_softmax(_a						,					axis=-1					)
										if target_ids is not None:
													lowerCamelCase      =   tf.gather_nd(tf.squeeze(_a						,					0					)						,					target_ids.reshape(-1						,					1					)					)
													lowerCamelCase      =   tf.expand_dims(_a						,					0					)

										lowerCamelCase      =   tf.math.top_k(_a						,					k=_a					)
										lowerCamelCase ,  lowerCamelCase      =   topk.values.numpy(), topk.indices.numpy()
							else:
										lowerCamelCase      =   torch.nonzero(input_ids == self.tokenizer.mask_token_id						,					as_tuple=_a					).squeeze(-1					)
										# Fill mask pipeline supports only one ${mask_token} per sample

										lowerCamelCase      =   outputs[0, masked_index, :]
										lowerCamelCase      =   logits.softmax(dim=-1					)
										if target_ids is not None:
													lowerCamelCase      =   probs[..., target_ids]

										lowerCamelCase ,  lowerCamelCase      =   probs.topk(_a					)

							lowerCamelCase      =   []
							lowerCamelCase      =   values.shape[0] == 1
							for i, (_values, _predictions) in enumerate(zip(values.tolist()						,					predictions.tolist()					)					):
										lowerCamelCase      =   []
										for v, p in zip(_values						,					_predictions					):
													# Copy is important since we're going to modify this array in place
													lowerCamelCase      =   input_ids.numpy().copy()
													if target_ids is not None:
																lowerCamelCase      =   target_ids[p].tolist()

													lowerCamelCase      =   p
													# Filter padding out:
													lowerCamelCase      =   tokens[np.where(tokens != self.tokenizer.pad_token_id					)]
													# Originally we skip special tokens to give readable output.
													# For multi masks though, the other [MASK] would be removed otherwise
													# making the output look odd, so we add them back
													lowerCamelCase      =   self.tokenizer.decode(_a						,					skip_special_tokens=_a					)
													lowerCamelCase      =   {"""score""": v, """token""": p, """token_str""": self.tokenizer.decode([p]					), """sequence""": sequence}
													row.append(_a					)
										result.append(_a					)
							if single_mask:
										return result[0]
							return result





				def   _lowerCAmelCase							(			self						,					_a						,					_a=None					):





							"""simple docstring"""
							if isinstance(_a						,					_a					):
										lowerCamelCase      =   [targets]
							try:
										lowerCamelCase      =   self.tokenizer.get_vocab()
							except Exception:
										lowerCamelCase      =   {}
							lowerCamelCase      =   []
							for target in targets:
										lowerCamelCase      =   vocab.get(_a						,					_a					)
										if id_ is None:
													lowerCamelCase      =   self.tokenizer(
													    _a						,					add_special_tokens=_a						,					return_attention_mask=_a						,					return_token_type_ids=_a						,					max_length=1						,					truncation=_a						,					)["""input_ids"""]
													if len(_a					) == 0:
																logger.warning(
																    f'The specified target token `{target}` does not exist in the model vocabulary. '
																    """We cannot replace it with anything meaningful, ignoring it"""					)
																continue
													lowerCamelCase      =   input_ids[0]
													# XXX: If users encounter this pass
													# it becomes pretty slow, so let's make sure
													# The warning enables them to fix the input to
													# get faster performance.
													logger.warning(
													    f'The specified target token `{target}` does not exist in the model vocabulary. '
													    f'Replacing with `{self.tokenizer.convert_ids_to_tokens(id_					)}`.'					)
										target_ids.append(id_					)
							lowerCamelCase      =   list(set(_a					)					)
							if len(_a					) == 0:
										raise ValueError("""At least one target must be provided when passed."""					)
							lowerCamelCase      =   np.array(_a					)
							return target_ids





				def   _lowerCAmelCase							(			self						,					_a=None						,					_a=None					):





							"""simple docstring"""
							lowerCamelCase      =   {}

							if targets is not None:
										lowerCamelCase      =   self.get_target_ids(_a						,					_a					)
										lowerCamelCase      =   target_ids

							if top_k is not None:
										lowerCamelCase      =   top_k

							if self.tokenizer.mask_token_id is None:
										raise PipelineException(
										    """fill-mask"""						,					self.model.base_model_prefix						,					"""The tokenizer does not define a `mask_token`."""					)
							return {}, {}, postprocess_params





				def __call__(			self						,					_a						,					*_a						,					**_a					):





							"""simple docstring"""
							lowerCamelCase      =   super().__call__(_a						,					**_a					)
							if isinstance(_a						,					_a					) and len(_a					) == 1:
										return outputs[0]
							return outputs



